JOURNAL ARTICLE

Incremental bearing fault diagnosis method under imbalanced sample conditions

Gezhi LiuLifeng Wu

Year: 2024 Journal:   Computers & Industrial Engineering Vol: 192 Pages: 110203-110203   Publisher: Elsevier BV
Keywords:
Fault (geology) Computer science Sample (material) Artificial intelligence Sampling (signal processing) Fault detection and isolation Data mining Process (computing) Machine learning Bearing (navigation) Sample size determination Classifier (UML) Set (abstract data type) Pattern recognition (psychology) Mathematics Statistics Computer vision

Metrics

25
Cited By
15.91
FWCI (Field Weighted Citation Impact)
39
Refs
0.99
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Machine Fault Diagnosis Techniques
Physical Sciences →  Engineering →  Control and Systems Engineering
Gear and Bearing Dynamics Analysis
Physical Sciences →  Engineering →  Mechanical Engineering
Engineering Diagnostics and Reliability
Physical Sciences →  Engineering →  Mechanics of Materials

Related Documents

JOURNAL ARTICLE

Physics-informed auto-encoder based on digital twin for rolling bearing fault diagnosis under imbalanced sample conditions

Zhiwu ShangZiyu WangCailu PanWanxiang LiMaosheng Gao

Journal:   Engineering Applications of Artificial Intelligence Year: 2025 Vol: 163 Pages: 113017-113017
JOURNAL ARTICLE

Fault Diagnosis of Rolling Bearing with Imbalanced Small Sample Scenarios

Yang GuanZong MengDengyun Sun

Journal:   2021 Global Reliability and Prognostics and Health Management (PHM-Nanjing) Year: 2021 Pages: 1-8
JOURNAL ARTICLE

CSWGAN-GP: A new method for bearing fault diagnosis under imbalanced condition

Xi GuYaoxiang YuLiang GuoHongli GaoMing Luo

Journal:   Measurement Year: 2023 Vol: 217 Pages: 113014-113014
© 2026 ScienceGate Book Chapters — All rights reserved.